The coordinated activity of large populations of neurons gives rise to sensation, perception, decision, and action. However, the rules by which these populations are coordinated are unknown. Only certain patterns of neural activity have meaning, whether sensory and motor-related or entirely internal and not overtly manifest. In the past few years we gained direct access to the activity of such large populations of neurons. For example, we can now routinely record and analyze neural populations of 10,000 neurons in the mammalian cortex. The richness of these recordings gives us a better chance to understand how distributed patterns of activity, across neurons, relate to the animal’s sensory experiences, and how they get transformed into motor actions.

The goal of our work is to understand how detailed high-dimensional patterns of neural activity encode the animal’s perception of the external world, and how those percepts are combined with pre-existing internal biases and learnt properties of the world to generate flexible behavior. We will achieve this goal by combining multi-sensory flexible behavioral paradigms and large-scale recording techniques.